Genetic risk factors for drug-induced long QT syndrome: findings from a large real-world case-control study

Aim: Drug-induced long QT syndrome (diLQTS), an adverse effect of many drugs, can lead to sudden cardiac death. Candidate genetic variants in cardiac ion channels have been associated with diLQTS, but several limitations of previous studies hamper clinical utility. Materials & methods: Thus, the purpose of this study was to assess the associations of KCNE1-D85N, KCNE2-I57T and SCN5A-G615E with diLQTS in a large observational case-control study (6,083 self-reported white patients treated with 27 different high-risk QT-prolonging medications; 12.0% with diLQTS). Results: KCNE1-D85N significantly associated with diLQTS (adjusted odds ratio: 2.24 [95% CI: 1.35-3.58]; p = 0.001). Given low minor allele frequencies, the study had insufficient power to analyze KCNE2-I57T and SCN5A-G615E. Conclusion: KCNE1-D85N is a risk factor for diLQTS that should be considered in future clinical practice guidelines.

Risk scores for major bleeding from direct oral anticoagulants: comparing predictive performance in patients with atrial fibrillation

Background

Despite direct oral anticoagulants (DOACs) being safer than warfarin for stroke prevention in atrial fibrillation (AF), major bleeding concerns persist. Most bleeding risk scores predate DOAC approval.

Objectives

This study aimed to compare the Age, history of Bleeding, and non-bleeding related Hospitalisation [ABH] score's performance-derived for DOAC-treated patients-with those of 5 other scores (Anticoagulation and Risk Factors in Atrial Fibrillation [ATRIA], Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly [>65 years], Drugs/alcohol concomitantly [HAS-BLED], Hepatic, Hepatic or Renal Disease, Ethanol Abuse, Malignancy, Older Age, Reduced Platelet Count or Function, Re-Bleeding, Hypertension, Anemia, Genetic Factors, Excessive Fall Risk and Stroke [HEMORR2HAGES], Outcomes Registry for Better Informed Treatment of Atrial Fibrillation [ORBIT-AF], and Congestive heart failure, Hypertension, Age ≥75 [doubled], Diabetes, Stroke [doubled]-Vascular disease, Age 65-74, Sex category [CHA2DS2-VASc]) in predicting DOAC-related major bleeding in patients with AF.

Methods

In this retrospective study of 2364 patients with nonvalvular AF on rivaroxaban or apixaban (median age, 68.3 years; 32.1% women), International Society on Thrombosis and Haemostasis-defined major bleeding (incidence, 4.1%; n = 97) was analyzed. C-statistics from time-dependent receiver operating characteristic (ROC) curves for continuous risk scores were the primary comparison metric, but other metrics, such as decision curves, were also compared.

Results

At 100 days, C-statistics were highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60); some significant differences favored ORBIT-AF. At 1100 days, C-statistics remained highest for ORBIT-AF and ATRIA (0.62 and 0.61, respectively, with other scores having an area under the ROC curve of <0.60 again), and ORBIT-AF had significantly higher C-statistics than those for all other risk scores (P < .05), except for ATRIA. At 2100 days, all C-statistics were <0.60 with no significant differences. Decision curves showed the greatest net benefit for ORBIT-AF and ATRIA at 100 days and for ATRIA at 1100 days, with no discernible net benefit for any of the scores at 2100 days.

Conclusion

ORBIT-AF and ATRIA provided the best bleeding risk prediction within the first 1100 days. None of the 6 bleeding risk scores provided predictive benefit over 2100 days of DOAC treatment.

Evaluation of a New Aptamer-Based Array for Soluble Suppressor of Tumorgenicity (ST2) and N-terminal Pro-B-Type Natriuretic Peptide (NTproBNP) in Heart Failure Patients

BACKGROUND

Recent advances in multi-marker platforms offer faster data generation, but the fidelity of these methods compared to the ELISA is not established. We tested the correlation and predictive performance of SOMAscan vs. ELISA methods for NTproBNP and ST2.

METHODS

Patients ≥ 18 years with heart failure and ejection fraction < 50% were enrolled. We tested the correlation between SOMA and ELISA for each biomarker and their association with outcomes.

RESULTS

There was good correlation of SOMA vs. ELISA for ST2 (ρ = 0.71) and excellent correlation for NTproBNP (ρ = 0.94). The two versions of both markers were not significantly different regarding survival association. The two ST2 assays and NTproBNP assays were similarly associated with all-cause mortality and cardiovascular mortality. These associations remained statistically significant when adjusted for MAGGIC risk score (all p < 0.05).

CONCLUSION

SOMAscan quantifications of ST2 and NTproBNP correlate to ELISA versions and carry similar prognosis.

Genome-Wide Association Study of Beta-Blocker Survival Benefit in Black and White Patients with Heart Failure with Reduced Ejection Fraction

In patients with heart failure with reduced ejection fraction (HFrEF), individual responses to beta-blockers vary. Candidate gene pharmacogenetic studies yielded significant but inconsistent results, and they may have missed important associations. Our objective was to use an unbiased genome-wide association study (GWAS) to identify loci influencing beta-blocker survival benefit in HFrEF patients. Genetic variant × beta-blocker exposure interactions were tested in Cox proportional hazards models for all-cause mortality stratified by self-identified race. The models were adjusted for clinical risk factors and propensity scores. A prospective HFrEF registry (469 black and 459 white patients) was used for discovery, and linkage disequilibrium (LD) clumped variants with a beta-blocker interaction of p < 5 × 10-5, were tested for Bonferroni-corrected validation in a multicenter HFrEF clinical trial (288 black and 579 white patients). A total of 229 and 18 variants in black and white HFrEF patients, respectively, had interactions with beta-blocker exposure at p < 5 × 10-5 upon discovery. After LD-clumping, 100 variants and 4 variants in the black and white patients, respectively, remained for validation but none reached statistical significance. In conclusion, genetic variants of potential interest were identified in a discovery-based GWAS of beta-blocker survival benefit in HFrEF patients, but none were validated in an independent dataset. Larger cohorts or alternative approaches, such as polygenic scores, are needed.

Common Variants on FGD5 Increase Hazard of Mortality or Rehospitalization in Patients With Heart Failure From the ASCEND-HF Trial

BACKGROUND

Heart failure remains a global health burden, and patients hospitalized are particularly at risk, but genetic associates for subsequent death or rehospitalization are still lacking.

METHODS

The genetic substudy of the ASCEND-HF trial (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) was used to perform genome-wide association study and transethnic meta-analysis. The overall trial included the patients of self-reported European ancestry (n=2173) and African ancestry (n=507). The end point was death or heart failure rehospitalization within 180 days. Cox models adjusted for 11 a priori predictors of rehospitalization and 5 genetic principal components were used to test the association between single-nucleotide polymorphisms and outcome. Summary statistics from the 2 populations were combined via meta-analysis with the significance threshold considered P<5×10-8.

RESULTS

Common variants (rs2342882 and rs35850039 in complete linkage disequilibrium) located in FGD5 were significantly associated with the primary outcome in both ancestry groups (European Americans: hazard ratio [HR], 1.38; P=2.42×10-6; African ancestry: HR, 1.51; P=4.43×10-3; HR in meta-analysis, 1.41; P=4.25×10-8). FGD5 encodes a regulator of VEGF (vascular endothelial growth factor)-mediated angiogenesis, and in silico investigation revealed several previous genome-wide association study hits in this gene, among which rs748431 was associated with our outcome (HR, 1.20; meta P<0.01). Sensitivity analysis proved FGD5 common variants survival association did not appear to operate via coronary artery disease or nesiritide treatment (P>0.05); and the signal was still significant when changing the censoring time from 180 to 30 days (HR, 1.39; P=1.59×10-5).

CONCLUSIONS

In this multiethnic genome-wide association study of ASCEND-HF, single-nucleotide polymorphisms in FGD5 were associated with increased risk of death or rehospitalization. Additional investigation is required to examine biological mechanisms and whether FGD5 could be a therapeutic target.

REGISTRATION

URL: https://www.

CLINICALTRIALS

gov; Unique identifier: NCT00475852.

An Introductory Tutorial on Cardiovascular Pharmacogenetics for Healthcare Providers

Pharmacogenetics can improve clinical outcomes by reducing adverse drug effects and enhancing therapeutic efficacy for commonly used drugs that treat a wide range of cardiovascular diseases. One of the major barriers to the clinical implementation of cardiovascular pharmacogenetics is limited education on this field for current healthcare providers and students. The abundance of pharmacogenetic literature underscores its promise, but it can also be challenging to learn such a wealth of information. Moreover, current clinical recommendations for cardiovascular pharmacogenetics can be confusing because they are outdated, incomplete, or inconsistent. A myriad of misconceptions about the promise and feasibility of cardiovascular pharmacogenetics among healthcare providers also has halted clinical implementation. Therefore, the main goal of this tutorial is to provide introductory education on the use of cardiovascular pharmacogenetics in clinical practice. The target audience is any healthcare provider (or student) with patients that use or have indications for cardiovascular drugs. This tutorial is organized into the following 6 steps: (1) understand basic concepts in pharmacogenetics; (2) gain foundational knowledge of cardiovascular pharmacogenetics; (3) learn the different organizations that release cardiovascular pharmacogenetic guidelines and recommendations; (4) know the current cardiovascular drugs/drug classes to focus on clinically and the supporting evidence; (5) discuss an example patient case of cardiovascular pharmacogenetics; and (6) develop an appreciation for emerging areas in cardiovascular pharmacogenetics. Ultimately, improved education among healthcare providers on cardiovascular pharmacogenetics will lead to a greater understanding for its potential in improving outcomes for a leading cause of morbidity and mortality.

Pharmacogenetics of Antiplatelet Therapy

Antiplatelet therapy is used in the treatment of patients with acute coronary syndromes, stroke, and those undergoing percutaneous coronary intervention. Clopidogrel is the most widely used antiplatelet P2Y12 inhibitor in clinical practice. Genetic variation in CYP2C19 may influence its enzymatic activity, resulting in individuals who are carriers of loss-of-function CYP2C19 alleles and thus have reduced active clopidogrel metabolites, high on-treatment platelet reactivity, and increased ischemic risk. Prospective studies have examined the utility of CYP2C19 genetic testing to guide antiplatelet therapy, and more recently published meta-analyses suggest that pharmacogenetics represents a key treatment strategy to individualize antiplatelet therapy. Rapid genetic tests, including bedside genotyping platforms that are validated and have high reproducibility, are available to guide selection of P2Y12 inhibitors in clinical practice. The aim of this review is to provide an overview of the background and rationale for the role of a guided antiplatelet approach to enhance patient care.

Eight pharmacokinetic genetic variants are not associated with the risk of bleeding from direct oral anticoagulants in non-valvular atrial fibrillation patients

Background: Atrial fibrillation (AF) is the leading cause of ischemic stroke and treatment has focused on reducing this risk through anticoagulation. Direct Oral Anticoagulants (DOACs) are the first-line guideline-recommended therapy since they are as effective and overall safer than warfarin in preventing AF-related stroke. Although patients bleed less from DOACs compared to warfarin, bleeding remains the primary safety concern with this therapy. Hypothesis: Genetic variants known to modify the function of metabolic enzymes or transporters involved in the pharmacokinetics (PK) of DOACs could increase the risk of bleeding. Aim: To assess the association of eight, functional PK-related single nucleotide variants (SNVs) in five genes (ABCB1, ABCG2, CYP2J2, CYP3A4, CYP3A5) with the risk of bleeding from DOACs in non-valvular AF patients. Methods: A retrospective cohort study was carried out with 2,364 self-identified white non-valvular AF patients treated with either rivaroxaban or apixaban. Genotyping was performed with Illumina Infinium CoreExome v12.1 bead arrays by the Michigan Genomics Initiative biobank. The primary endpoint was a composite of major and clinically relevant non-major bleeding. Cox proportional hazards regression with time-varying analysis assessed the association of the eight PK-related SNVs with the risk of bleeding from DOACs in unadjusted and covariate-adjusted models. The pre-specified primary analysis was the covariate-adjusted, additive genetic models. Six tests were performed in the primary analysis as three SNVs are in the same haplotype, and thus p-values below the Bonferroni-corrected level of 8.33e-3 were considered statistically significant. Results: In the primary analysis, none of the SNVs met the Bonferroni-corrected level of statistical significance (all p > 0.1). In exploratory analyses with other genetic models, the ABCB1 (rs4148732) GG genotype tended to be associated with the risk of bleeding from rivaroxaban [HR: 1.391 (95%CI: 1.019-1.900); p = 0.038] but not from apixaban (p = 0.487). Conclusion: Eight functional PK-related genetic variants were not significantly associated with bleeding from either rivaroxaban or apixaban in more than 2,000 AF self-identified white outpatients.

Clinical Pharmacogenetics Implementation Consortium Guideline for CYP2C19 Genotype and Clopidogrel Therapy: 2022 Update

CYP2C19 catalyzes the bioactivation of the antiplatelet prodrug clopidogrel, and CYP2C19 genotype impacts clopidogrel active metabolite formation. CYP2C19 intermediate and poor metabolizers who receive clopidogrel experience reduced platelet inhibition and increased risk for major adverse cardiovascular and cerebrovascular events. This guideline is an update to the 2013 Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for the use of clopidogrel based on CYP2C19 genotype and includes expanded indications for CYP2C19 genotype-guided antiplatelet therapy, increased strength of recommendation for CYP2C19 intermediate metabolizers, updated CYP2C19 genotype to phenotype translation, and evidence from an expanded literature review (updates at www.cpicpgx.org).

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Coenzyme Q10 supplementation for the treatment of statin-associated muscle symptoms

Aim: To determine the association of coenzyme Q10 (CoQ10) use with the resolution of statin-associated muscle symptoms (SAMS). Patients & methods: Retrospective analysis of a large, multicenter survey study of SAMS (total n = 511; n = 64 CoQ10 users). Univariate and multivariate logistic regression models assessed the association between CoQ10 use and the resolution of SAMS. Results: The frequency of SAMS resolution was similar between CoQ10 users and non-users (25% vs 31%, respectively; unadjusted odds ratio [OR]: 0.75 [95% CI: 0.41-1.38]; p = 0.357). Similarly, CoQ10 use was not significantly associated with the resolution of SAMS in multivariable models adjusted for SAMS risk factors (OR: 0.84 [95% CI: 0.45-1.55]; p = 0.568) or adjusted for significant differences among CoQ10 users and non-users (OR: 0.82 [95% CI: 0.45-1.51]; p = 0.522). Conclusion: CoQ10 was not significantly associated with the resolution of SAMS.

The genetics of drug-induced QT prolongation: evaluating the evidence for pharmacodynamic variants

Drug-induced long QT syndrome (diLQTS) is an adverse effect of many commonly prescribed drugs, and it can increase the risk for lethal ventricular arrhythmias. Genetic variants in pharmacodynamic genes have been associated with diLQTS, but the strength of the evidence for each of those variants has not yet been evaluated. Therefore, the purpose of this review was to evaluate the strength of the evidence for pharmacodynamic genetic variants associated with diLQTS using a novel, semiquantitative scoring system modified from the approach used for congenital LQTS. KCNE1-D85N and KCNE2-T8A had definitive and strong evidence for diLQTS, respectively. The high level of evidence for these variants supports current consideration as risk factors for patients that will be prescribed a QT-prolonging drug.

The Clinical Pharmacogenetics Implementation Consortium (CPIC) guideline for SLCO1B1, ABCG2 , and CYP2C9 and statin‐associated musculoskeletal symptoms

Statins reduce cholesterol, prevent cardiovascular disease, and are among the most commonly prescribed medications in the world. Statin-associated musculoskeletal symptoms (SAMS) impact statin adherence and ultimately can impede the long-term effectiveness of statin therapy. There are several identified pharmacogenetic variants that impact statin disposition and adverse events during statin therapy. SLCO1B1 encodes a transporter (SLCO1B1; alternative names include OATP1B1 or OATP-C) that facilitates the hepatic uptake of all statins. ABCG2 encodes an efflux transporter (BCRP) that modulates the absorption and disposition of rosuvastatin. CYP2C9 encodes a phase I drug metabolizing enzyme responsible for the oxidation of some statins. Genetic variation in each of these genes alters systemic exposure to statins (i.e., simvastatin, rosuvastatin, pravastatin, pitavastatin, atorvastatin, fluvastatin, lovastatin), which can increase the risk for SAMS. We summarize the literature supporting these associations and provide therapeutic recommendations for statins based on SLCO1B1, ABCG2, and CYP2C9 genotype with the goal of improving the overall safety, adherence, and effectiveness of statin therapy. This document replaces the 2012 and 2014 Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for SLCO1B1 and simvastatin-induced myopathy.

Comparison of clinical pharmacogenetic recommendations across therapeutic areas

OBJECTIVES

Evaluations from pharmacogenetics implementation programs at major US medical centers have reported variability in the clinical adoption of pharmacogenetics across therapeutic areas. A potential cause for this variability may involve therapeutic area-specific differences in published pharmacogenetics recommendations to clinicians. To date, however, the potential for differences in clinical pharmacogenetics recommendations by therapeutic areas from prominent US guidance sources has not been assessed. Accordingly, our objective was to comprehensively compare essential elements from clinical pharmacogenetics recommendations contained within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and clinical practice guidelines from US professional medical organizations across therapeutic areas.

METHODS

We analyzed clinical pharmacogenetics recommendation elements within Clinical Pharmacogenetics Implementation Consortium guidelines, US Food and Drug Administration drug labels and professional clinical practice guidelines through 05/24/19.

RESULTS

We identified 606 unique clinical pharmacogenetics recommendations, with the most recommendations involving oncology (217 recommendations), hematology (79), psychiatry (65), cardiovascular (43) and anesthetic (37) medications. Within our analyses, we observed considerable variability across therapeutic areas within the following essential pharmacogenetics recommendation elements: the recommended clinical management strategy; the relevant genetic biomarkers; the organizations providing pharmacogenetics recommendations; whether routine genetic screening was recommended; and the time since recommendations were published.

CONCLUSIONS

On the basis of our results, we infer that observed differences in clinical pharmacogenetics recommendations across therapeutic areas may result from specific factors associated with individual disease states, the associated genetic biomarkers, and the characteristics of the organizations providing recommendations.

Association of Valproic Acid Use With Post-Myocardial Infarction Heart Failure Development: A Meta-Analysis of Two Retrospective Case-Control Studies

BACKGROUND

Despite advances in treatments, myocardial infarction (MI) remains a significant cause of morbidity and mortality worldwide. Our team has previously shown that valproic acid (VPA) is cardio-protective when administered to rats post-MI. The aim of this study was to investigate the association of VPA use with post-MI heart failure (HF) development in humans.

METHODS

This study was a random effects meta-analysis of two retrospective case-control studies collected from electronic health record (Michigan Medicine) and claims data (OptumInsight). Cases with an active prescription for VPA at the time of their MI were matched 1:4 to controls not taking VPA at the time of their MI by multiple demographic and clinical characteristics. The primary outcome, time-to-HF development, was analyzed using the Fine-Gray competing risks model of any VPA prescription versus no VPA prescription. An exploratory analysis was conducted to evaluate the association of different VPA doses (≥1000 mg/day vs <1000 mg/day vs 0 mg/day VPA).

RESULTS

In total, the datasets included 1313 patients (249 cases and 1064 controls). In the meta-analysis, any dose of VPA during an MI tended to be protective against incident HF post-MI (HR = 0.87; 95% CI = 0.72-1.01). However, when stratified by dose, high-dose VPA (≥1000 mg/day) significantly associated with 30% reduction in risk for HF post-MI (HR = 0.70; 95% CI = 0.49-0.91), whereas low-dose VPA (<1000 mg/day) did not (HR = 0.95; 95% CI = 0.78-1.13).

CONCLUSION

VPA doses ≥1000 mg/day may provide post-MI cardio-protection resulting in a reduced incidence of HF.

Pharmacogenetic study in gastric cancer patients treated with adjuvant fluorouracil/leucovorin or epirubicin/cisplatin/fluorouracil before and after chemoradiation on CALGB 80101 (Alliance)

There is a lack of pharmacogenetic predictors of outcome in gastric cancer patients. The aim of this study was to assess previously identified candidate genes associated with 5-fluorouracil (5-FU), cisplatin, or epirubicin toxicity or response in a cohort of resected gastric cancer patients treated on CALGB (Alliance) 80101. Gastric or gastroesophageal cancer patients randomized to adjuvant 5-FU/leucovorin or epirubicin/cisplatin/5-FU before and after 5-FU chemoradiation were genotyped for single nucleotide polymorphisms (SNPs) in GSTP1 (rs1695), ERCC1 (rs11615 and rs3212986), XRCC1 (rs25487), UGT2B7 (rs7439366) and the 28 base-pair tandem repeats in TYMS (rs34743033). Logistic regression and log rank tests were used to assess the association between each SNP and incidence of grade 3/4 neutropenia and leukopenia, overall (OS) and progression-free survival (PFS), respectively. Toxicity endpoint analyses were adjusted for the treatment arm, while OS and PFS were also adjusted for performance status, sex, age, lymph node involvement, and primary tumor site and size. Of 281 subjects with successful genotyping results and available clinical (toxicity and efficacy) data, 166 self-reported non-Hispanic White patients were included in the final analysis. There was a lack of evidence of an association among any SNPs tested with grade 3/4 neutropenia and leukopenia or OS and PFS. Age, lymph node involvement, and primary tumor size were significantly associated with OS and PFS. This study failed to confirm results of previous gastric cancer pharmacogenetic studies.

The need to shift pharmacogenetic research from candidate gene to genome-wide association studies

The primary research approach in pharmacogenetics has been candidate gene association studies (CGAS), but pharmacogenomic genome-wide association studies (GWAS) are becoming more common. We are now at a critical juncture when the results of those two research approaches, CGAS and GWAS, can be compared in pharmacogenetics. We analyzed publicly available databases of pharmacogenetic CGAS and GWAS (i.e., the Pharmacogenomics Knowledgebase [PharmGKB^®] and the NHGRI-EBI GWAS catalog) and the vast majority of variants (98%) and genes (94%) discovered in pharmacogenomic GWAS were novel (i.e., not previously studied CGAS). Therefore, pharmacogenetic researchers are not selecting the right candidate genes in the vast majority of CGAS, highlighting a need to shift pharmacogenetic research efforts from CGAS to GWAS.

Comparative performance of the two pooled cohort equations for predicting atherosclerotic cardiovascular disease

BACKGROUND AND AIMS

Multivariable algorithms have been developed to predict the risk of atherosclerotic cardiovascular disease (ASCVD) to identify high-risk patients. Shortly after the introduction of the AHA/ACC Pooled Cohort Equations (PCE), a systematic overestimation of risk was identified. As such, a revised PCE was proposed to more accurately assess ASCVD risk. This study aims to compare the accuracy of both PCE in predicting ASCVD risk within a large, real-world patient sample in the US.

METHODS

This retrospective cohort study identified 20,843 patients aged between 40 and 75 years with no previous ASCVD in an academic healthcare system. Model fit, calibration, and discrimination were compared between PCE using Bayesian Information Criterion (BIC), Hosmer-Lemeshow test, area under the ROC curves (AUC), Brier score, and precision-recall analysis. In addition, we examined race and sex subgroups for effect modification.

RESULTS

Both PCE showed poor calibration (Hosmer-Lemeshow χ² > 20; p < 0.05) and discrimination (AUC<0.7). The lack of improvement in discrimination of the revised PCE (AUC: 0.677 vs 0.679; p = 0.357) was confirmed with the AUC precision-recall curves (AUC_PR: 0.0717 vs 0.0698). In contrast, the AHA/ACC PCE showed a strong positive risk prediction (ΔBIC>10) compared to the revised PCE, although calibration curves had overlapped.

CONCLUSIONS

In this single center analysis, both PCE had poor calibration and discrimination of ASCVD risk in a large, real-world patient sample followed up for over 2 years. There was no evidence of improvement in the accuracy of the revised PCE in assessing the risk of ASCVD in relation to the AHA/ACC PCE.

Moving Pharmacogenetics Into Practice: It's All About the Evidence!

The evidence for pharmacogenetics has grown rapidly in recent decades. However, the strength of evidence required for the clinical implementation of pharmacogenetics is highly debated. Therefore, the purpose of this review is to summarize different perspectives on the evidence required for the clinical implementation of pharmacogenetics. First, we present two patient cases that demonstrate how knowledge of pharmacogenetic evidence affected their care. Then we summarize resources that curate pharmacogenetic evidence, types of evidence (with an emphasis on randomized controlled trials [RCT]) and their limitations, and different perspectives from implementers, clinicians, and patients. We compare pharmacogenetics to a historical example (i.e., the evidence required for the clinical implementation of pharmacokinetics/therapeutic drug monitoring), and we provide future perspectives on the evidence for pharmacogenetic panels and the need for more education in addition to evidence. Although there are differences in the interpretation of pharmacogenetic evidence across resources, efforts for standardization are underway. Survey data illustrate the value of pharmacogenetic testing from the patient perspective, with their providers seen as key to ensuring maximum benefit from test results. However, clinicians and practice guidelines from medical societies often rely on RCT data to guide treatment decisions, which are not always feasible or ethical in pharmacogenetics. Thus, recognition of other types of evidence to support pharmacogenetic implementation is needed. Among pharmacogenetic implementers, consistent evidence of pharmacogenetic associations is deemed most critical. Ultimately, moving pharmacogenetics into practice will require consideration of multiple stakeholder perspectives, keeping particularly attuned to the voice of the ultimate stakeholder-the patient.

Prevalence and types of inconsistencies in clinical pharmacogenetic recommendations among major U.S. sources

Clinical implementation of pharmacogenomics (PGx) is slow. Previous studies have identified some inconsistencies among clinical PGx recommendations, but the prevalence and types of inconsistencies have not been comprehensively analyzed among major PGx guidance sources in the U.S. PGx recommendations from the Clinical Pharmacogenetics Implementation Consortium, U.S. Food and Drug Administration drug labels, and major U.S. professional medical organizations were analyzed through May 24, 2019. Inconsistencies were analyzed within the following elements: recommendation category; whether routine screening was recommended; and the specific biomarkers, variants, and patient groups involved. We identified 606 total clinical PGx recommendations, which contained 267 unique drugs. Composite inconsistencies occurred in 48.1% of clinical PGx recommendations overall, and in 93.3% of recommendations from three sources. Inconsistencies occurred in the recommendation category (29.8%), the patient group (35.4%), and routine screening (15.2%). In conclusion, almost one-half of clinical PGx recommendations from prominent U.S. guidance sources contain inconsistencies, which can potentially slow clinical implementation.

Polygenic Score for β-Blocker Survival Benefit in European Ancestry Patients With Reduced Ejection Fraction Heart Failure

BACKGROUND

β-Blockers (BBs) are mainstay therapy for heart failure with reduced ejection fraction. However, individual patient responses to BB vary, which may be partially due to genetic variation. The goal of this study was to derive and validate the first polygenic response predictor (PRP) for BB survival benefit in heart failure with reduced ejection fraction patients.

METHODS

Derivation and validation analyses were performed in n=1436 total HF patients of European descent and with ejection fraction <50%. The PRP was derived in a random subset of the Henry Ford Heart Failure Pharmacogenomic Registry (n=248) and then validated in a meta-analysis of the remaining patients from Henry Ford Heart Failure Pharmacogenomic Registry (n=247), the TIME-CHF (Trial of Intensified Versus Standard Medical Therapy in Elderly Patients With Congestive Heart Failure; n=431), and HF-ACTION trial (Heart Failure: a Controlled Trial Investigating Outcomes of Exercise Training; n=510). The PRP was constructed from a genome-wide analysis of BB×genotype interaction predicting time to all-cause mortality, adjusted for Meta-Analysis Global Group in Chronic Heart Failure score, genotype, level of BB exposure, and BB propensity score.

RESULTS

Five-fold cross-validation summaries out to 1000 single-nucleotide polymorphisms identified optimal prediction with a 44 single-nucleotide polymorphism score and cutoff at the 30th percentile. In validation testing (n=1188), greater BB exposure was associated with reduced all-cause mortality in patients with low PRP score (n=251; hazard ratio, 0.19 [95% CI, 0.04-0.51]; P=0.0075) but not high PRP score (n=937; hazard ratio, 0.84 [95% CI, 0.53-1.3]; P=0.448)-a difference that was statistically significant (P interaction, 0.0235). Results were consistent regardless of atrial fibrillation, ejection fraction (≤40% versus 41%-50%), or when examining cardiovascular death.

CONCLUSIONS

Among patients of European ancestry with heart failure with reduced ejection fraction, a PRP distinguished patients who derived substantial survival benefit from BB exposure from a larger group that did not. Additional work is needed to prospectively test clinical utility and to develop PRPs for other population groups and other medications.

Pharmacogenomics of COVID-19 therapies

A new global pandemic of coronavirus disease 2019 (COVID-19) has resulted in high mortality and morbidity. Currently numerous drugs are under expedited investigations without well-established safety or efficacy data. Pharmacogenomics may allow individualization of these drugs thereby improving efficacy and safety. In this review, we summarized the pharmacogenomic literature available for COVID-19 drug therapies including hydroxychloroquine, chloroquine, azithromycin, remdesivir, favipiravir, ribavirin, lopinavir/ritonavir, darunavir/cobicistat, interferon beta-1b, tocilizumab, ruxolitinib, baricitinib, and corticosteroids. We searched PubMed, reviewed the Pharmacogenomics Knowledgebase (PharmGKB®) website, Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines, the U.S. Food and Drug Administration (FDA) pharmacogenomics information in the product labeling, and the FDA pharmacogenomics association table. We found several drug-gene variant pairs that may alter the pharmacokinetics of hydroxychloroquine/chloroquine (CYP2C8, CYP2D6, SLCO1A2, and SLCO1B1); azithromycin (ABCB1); ribavirin (SLC29A1, SLC28A2, and SLC28A3); and lopinavir/ritonavir (SLCO1B1, ABCC2, CYP3A). We also identified other variants, that are associated with adverse effects, most notable in hydroxychloroquine/chloroquine (G6PD; hemolysis), ribavirin (ITPA; hemolysis), and interferon β -1b (IRF6; liver toxicity). We also describe the complexity of the risk for QT prolongation in this setting because of additive effects of combining more than one QT-prolonging drug (i.e., hydroxychloroquine/chloroquine and azithromycin), increased concentrations of the drugs due to genetic variants, along with the risk of also combining therapy with potent inhibitors. In conclusion, although direct evidence in COVID-19 patients is lacking, we identified potential actionable genetic markers in COVID-19 therapies. Clinical studies in COVID-19 patients are deemed warranted to assess potential roles of these markers.

Association of Regulatory Genetic Variants for Protein Kinase Cα with Mortality and Drug Efficacy in Patients with Heart Failure

PURPOSE

Protein kinase C alpha (gene: PRKCA) is a key regulator of cardiac contractility. Two genetic variants have recently been discovered to regulate PRKCA expression in failing human heart tissue (rs9909004 [T → C] and rs9303504 [C → G]). The association of those variants with clinical outcomes in patients with heart failure (HF), and their interaction with HF drug efficacy, is unknown.

METHODS

Patients with HF in a prospective registry starting in 2007 were genotyped by whole genome array (n = 951). The primary outcome was all-cause mortality. Cox proportional hazards models adjusted for established clinical risk factors and genomic ancestry tested the independent association of rs9909004 or rs9303504 and the variant interactions with cornerstone HF pharmacotherapies (beta-blockers or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers) in additive genetic models.

RESULTS

The minor allele of rs9909004, but not of rs9303504, was independently associated with a decreased risk for all-cause mortality: adjusted HR = 0.81 (95% CI = 0.67-0.98), p = 0.032. The variants did not significantly interact with mortality benefit associated with cornerstone HF pharmacotherapies (p > 0.1 for all).

CONCLUSIONS

A recently discovered cardiac-specific regulatory variant for PRKCA (rs9909004) was independently associated with a decreased risk for all-cause mortality in patients with HF. The variant did not interact with mortality benefit associated with cornerstone HF pharmacotherapies.

Clinical features related to statin-associated muscle symptoms

INTRODUCTION

Statins reduce cardiovascular disease risk and are generally well tolerated, yet up to 0.5% of statin-treated patients develop incapacitating muscle symptoms including rhabdomyolysis. Our objective was to identify clinical factors related to statin-associated muscle symptoms (SAMS).

METHODS

Clinical and laboratory characteristics were evaluated in 748 statin-treated Caucasians (634 with SAMS and 114 statin-tolerant controls). Information was collected on statin type, concomitant drug therapies, muscle symptom history, comorbidities, and family history. Logistic regression was used to identify associations.

RESULTS

Individuals with SAMS were 3.6 times (odds ratio [OR] 3.60, 95% confidence interval [CI] 2.08-6.22) more likely than statin-tolerant controls to have a family history of heart disease. Additional associations included obesity (OR 3.08, 95% CI 1.18, 8.05), hypertension (OR 2.24, 95% CI 1.33, 3.77), smoking (OR 2.08, 95% CI 1.16, 3.74), and statin type.

DISCUSSION

Careful medical monitoring of statin-treated patients with the associated coexisting conditions may ultimately reduce muscle symptoms and lead to improved compliance. Muscle Nerve 59:537-537, 2019.

Does cardiology hold pharmacogenetics to an inconsistent standard? A comparison of evidence among recommendations

Current guideline recommendations for pharmacogenetic testing for clopidogrel by the American Heart Association/American College of Cardiology (AHA/ACC) contradict the Clinical Pharmacogenetics Implementation Consortium and the US FDA. The AHA/ACC recommends against routine pharmacogenetic testing for clopidogrel because no randomized controlled trials have demonstrated that testing improves patients' outcomes. However the AHA/ACC and the National Comprehensive Cancer Network (NCCN) recommend other pharmacogenetic tests in the absence of randomized controlled trials evidence. Using clopidogrel as a case example, we compared the evidence for other pharmacogenetic tests recommended by the AHA/ACC and NCCN. In patients that received percutaneous coronary intervention, the evidence supporting pharmacogenetic testing for clopidogrel is stronger than other pharmacogenetic tests recommended by the AHA/ACC and NCCN.

Race and Beta-Blocker Survival Benefit in Patients With Heart Failure: An Investigation of Self-Reported Race and Proportion of African Genetic Ancestry

Background

It remains unclear whether beta‐blockade is similarly effective in black patients with heart failure and reduced ejection fraction as in white patients, but self‐reported race is a complex social construct with both biological and environmental components. The objective of this study was to compare the reduction in mortality associated with beta‐blocker exposure in heart failure and reduced ejection fraction patients by both self‐reported race and by proportion African genetic ancestry.

Methods and Results

Insured patients with heart failure and reduced ejection fraction (n=1122) were included in a prospective registry at Henry Ford Health System. This included 575 self‐reported blacks (129 deaths, 22%) and 547 self‐reported whites (126 deaths, 23%) followed for a median 3.0 years. Beta‐blocker exposure (BBexp) was calculated from pharmacy claims, and the proportion of African genetic ancestry was determined from genome‐wide array data. Time‐dependent Cox proportional hazards regression was used to separately test the association of BBexp with all‐cause mortality by self‐reported race or by proportion of African genetic ancestry. Both sets of models were evaluated unadjusted and then adjusted for baseline risk factors and beta‐blocker propensity score. BBexp effect estimates were protective and of similar magnitude both by self‐reported race and by African genetic ancestry (adjusted hazard ratio=0.56 in blacks and adjusted hazard ratio=0.48 in whites). The tests for interactions with BBexp for both self‐reported race and for African genetic ancestry were not statistically significant in any model (P>0.1 for all).

Conclusions

Among black and white patients with heart failure and reduced ejection fraction, reduction in all‐cause mortality associated with BBexp was similar, regardless of self‐reported race or proportion African genetic ancestry.

The pharmacoepigenomics informatics pipeline defines a pathway of novel and known warfarin pharmacogenomics variants

AIM

'Pharmacoepigenomics' methods informed by omics datasets and pre-existing knowledge have yielded discoveries in neuropsychiatric pharmacogenomics. Now we evaluate the generality of these methods by discovering an extended warfarin pharmacogenomics pathway.

MATERIALS & METHODS

We developed the pharmacoepigenomics informatics pipeline, a scalable multi-omics variant screening pipeline for pharmacogenomics, and conducted an experiment in the genomics of warfarin.

RESULTS

We discovered known and novel pharmacogenomics variants and genes, both coding and regulatory, for warfarin response, including adverse events. Such genes and variants cluster in a warfarin response pathway consolidating known and novel warfarin response variants and genes.

CONCLUSION

These results can inform a new warfarin test. The pharmacoepigenomics informatics pipeline may be able to discover new pharmacogenomics markers in other drug-disease systems.

Germline genetic variants with implications for disease risk and therapeutic outcomes

Genetic testing has multiple clinical applications including disease risk assessment, diagnosis, and pharmacogenomics. Pharmacogenomics can be utilized to predict whether a pharmacologic therapy will be effective or to identify patients at risk for treatment-related toxicity. Although genetic tests are typically ordered for a distinct clinical purpose, the genetic variants that are found may have additional implications for either disease or pharmacology. This review will address multiple examples of germline genetic variants that are informative for both disease and pharmacogenomics. The discussed relationships are diverse. Some of the agents are targeted for the disease-causing genetic variant, while others, although not targeted therapies, have implications for the disease they are used to treat. It is also possible that the disease implications of a genetic variant are unrelated to the pharmacogenomic implications. Some of these examples are considered clinically actionable pharmacogenes, with evidence-based, pharmacologic treatment recommendations, while others are still investigative as areas for additional research. It is important that clinicians are aware of both the disease and pharmacogenomic associations of these germline genetic variants to ensure patients are receiving comprehensive personalized care.

The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Outcomes and Metrics of Pharmacogenetic Implementations Across Diverse Healthcare Systems

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real-world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene-drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

Clinical pharmacogenomics: patient perspectives of pharmacogenomic testing and the incidence of actionable test results in a chronic disease cohort

Aim

This study aimed to examine pharmacogenomic test results and patient perspectives at an academic cardiovascular medicine clinic.

Patients & methods

Test results for three common cardiovascular drug-gene tests (warfarin-CYP2C9-VKORC1, clopidogrel-CYP2C19 and simvastatin-SLCO1B1) of 208 patients in the Ohio State University-Coriell Personalized Medicine Collaborative were examined to determine the incidence of potentially actionable test results. A post-hoc, anonymous, patient survey was also conducted.

Results

Potentially actionable test results for at least one of the three drug-gene tests were determined in 170 (82%) patients. Survey responses (n = 134) suggested that patients generally considered their test results to be important (median of 7.5 on a 10-point scale of importance) and were interested (median of 7.3 on a 10-point scale of interest) in a Clinical Pharmacogenomic Service.

Conclusion

Attitudes toward pharmacogenomic testing were generally favorable, and potentially actionable test results were not uncommon in this cardiovascular medicine cohort.

Institutional profile of pharmacogenetics within University of Michigan College of Pharmacy

The University of Michigan College of Pharmacy has made substantial investment in the area of pharmacogenomics to further bolster its activity in pharmacogenomics research, implementation and education. Four tenure-track faculty members have active research programs that focus primarily on the discovery of functional polymorphisms (HJ Zhu), and genetic associations with treatment outcomes in patients with cancer (DL Hertz), cardiovascular disease (JA Luzum) and psychiatric conditions (VL Ellingrod). Recent investments from the University and the College have accelerated the implementation of pharmacogenetics broadly across the institution and in targeted therapeutic areas. Students within the PharmD and other health science professions receive substantial instruction in pharmacogenomics, in preparation for careers in biomedical health in which they can contribute to the generation, dissemination and utilization of pharmacogenomics knowledge to improve patient care.

CYP2D6 Genetic Variation and Beta-Blocker Maintenance Dose in Patients with Heart Failure

PURPOSE

This study examined whether a CYP2D6 polymorphism (CYP2D6*4) was related to beta-blocker maintenance dose in patients with heart failure.

METHODS

Logistic regression modeling was utilized in a retrospective chart-review analysis of heart-failure patients (60% Male, 90% of European descent) to assess whether CYP2D6*4 (non-functional CYP2D6 allele present in 1 of 5 individuals of European descent) is associated with maintenance dose of carvedilol (n = 65) or metoprolol (n = 33).

RESULTS

CYP2D6*4 was associated with lower maintenance dose of metoprolol (OR 0.13 [95% CI 0.02-0.75] p = 0.023), and a trend was observed between CYP2D6*4 and higher maintenance dose of carvedilol (OR 2.94 [95% CI 0.84-10.30] p = 0.093). None of the patients that carried CYP2D6*4 achieved the recommended target dose of metoprolol (200 mg/day).

CONCLUSION

Consistent with the role of CYP2D6 in the metabolism of metoprolol, the tolerated maintenance dose of metoprolol was lower in CYP2D6*4 carriers compared to non-carriers. Consistent with the role of CYP2D6 in activation of carvedilol, tolerated maintenance dose of carvedilol was higher in CYP2D6*4 carriers compared to non-carriers. Further investigation is warranted to ascertain the potential of CYP2D6 as a potential predictive biomarker of beta-blocker maintenance dose in heart failure patients.

Candidate-Gene Study of Functional Polymorphisms in SLCO1B1 and CYP3A4/5 and the Cholesterol-Lowering Response to Simvastatin

Cholesterol‐lowering response to 40 mg simvastatin daily for 6 weeks was examined for associations with common genetic polymorphisms in key genes affecting simvastatin metabolism (CYP3A4 and CYP3A5) and transport (SLCO1B1). In white people (n = 608), SLCO1B1 521C was associated with lesser reductions of total and low‐density lipoprotein cholesterol. Associations between SLCO1B1 521C and cholesterol response were not detected in African Americans (n = 333). Associations between CYP3A4*22 or CYP3A5*3 and cholesterol response were not detected in either race, and no significant race‐gene or gene‐gene interactions were detected. As several of the analyses may have been underpowered (especially the analyses in the African American cohort), the findings not suggesting an association should not be considered conclusive and warrant further investigation. The finding regarding SLCO1B1 521C in whites was consistent with several previous reports. SLCO1B1 521C resulted in a diminished cholesterol‐lowering response, but a marginal effect size limits utility for predicting simvastatin response.

Pharmacogenomics of statins: understanding susceptibility to adverse effects

Statins are a cornerstone of the pharmacologic treatment and prevention of atherosclerotic cardiovascular disease. Atherosclerotic disease is a predominant cause of mortality and morbidity worldwide. Statins are among the most commonly prescribed classes of medications, and their prescribing indications and target patient populations have been significantly expanded in the official guidelines recently published by the American and European expert panels. Adverse effects of statin pharmacotherapy, however, result in significant cost and morbidity and can lead to nonadherence and discontinuation of therapy. Statin-associated muscle symptoms occur in ~10% of patients on statins and constitute the most commonly reported adverse effect associated with statin pharmacotherapy. Substantial clinical and nonclinical research effort has been dedicated to determining whether genetics can provide meaningful insight regarding an individual patient’s risk of statin adverse effects. This contemporary review of the relevant clinical research on polymorphisms in several key genes that affect statin pharmacokinetics (eg, transporters and metabolizing enzymes), statin efficacy (eg, drug targets and pathways), and end-organ toxicity (eg, myopathy pathways) highlights several promising pharmacogenomic candidates. However, SLCO1B1 521C is currently the only clinically relevant pharmacogenetic test regarding statin toxicity, and its relevance is limited to simvastatin myopathy.

Physicians' attitudes toward pharmacogenetic testing before and after pharmacogenetic education

AIM

Our aim was to evaluate physicians' attitudes toward pharmacogenetic testing before and after pharmacogenetic education.

METHODS

In total, 12 physicians (˜40% response rate) completed a survey with eight questions on 10-point scales on their attitudes toward pharmacogenetic testing before and after a 1-h grand rounds presentation on pharmacogenetics. Differences in question scores overall, among training levels (resident/fellow/attending), and specific drugs (clopidogrel/simvastatin/warfarin) were assessed using Wilcoxon signed-rank and exact Kruskal-Wallis tests.

RESULTS & CONCLUSION

The scores for all eight questions increased, with statistically significant (p < 0.05) increases for four out of eight questions. The scores were similar among training levels, but the postscores for clopidogrel were significantly higher than for simvastatin and warfarin. In conclusion, brief pharmacogenetic education can significantly affect physicians' attitudes toward pharmacogenetic testing.

GATM polymorphism associated with the risk for statin-induced myopathy does not replicate in case-control analysis of 715 dyslipidemic individuals

Statin-induced myopathy (SIM) is the most common reason for discontinuation of statin therapy. A polymorphism affecting the gene encoding glycine amidinotransferase (GATM rs9806699 G > A) was previously associated with reduced risk for SIM. Our objective was to replicate the GATM association in a large, multicenter SIM case-control study. Mild and severe SIM cases and age- and gender-matched controls were enrolled. Participants were genotyped, and associations were tested (n = 715) using chi-square and logistic regression with consideration for SIM severity and exclusion of subjects with potentially confounding comedications. The minor allele (A) frequencies of GATM rs9806699 in the controls (n = 106), mild SIM (n = 324), and severe SIM (n = 285) cases were 0.26, 0.28, and 0.29, respectively (p = 0.447). The unadjusted odds ratio for the A allele for any SIM (mild or severe) was 1.14 (0.82-1.61; p = 0.437), which remained nonsignificant in all models. Our results do not replicate the association between GATM rs9806699 and SIM.

Liquid chromatography-tandem mass spectrometry assay for the simultaneous quantification of simvastatin, lovastatin, atorvastatin, and their major metabolites in human plasma

Millions of individuals are treated with a variety of statins that are metabolized to a variety of active metabolites. A single assay capable of simultaneously quantifying commonly used statins and their major metabolites has not been previously reported. Herein we describe the development and validation of a novel and robust liquid chromatography-tandem mass spectrometry assay for simultaneously quantifying simvastatin, lovastatin, atorvastatin, and their metabolites, simvastatin acid, lovastatin acid, para-hydroxy atorvastatin, and ortho-hydroxy atorvastatin in human plasma. Plasma samples were processed with a simple protein precipitation technique using acetonitrile, followed by chromatographic separation using an Agilent Zorbax Extend C18 column. A 12.0min linear gradient elution was used at a flow rate of 400μL/min with a mobile phase of water and methanol, both modified with 2mM ammonium formate and 0.2% formic acid. The analytes and internal standard, hesperetin, were detected using the selected reaction monitoring mode on a TSQ Quantum Discovery mass spectrometer with positive electrospray ionization. The assay exhibited a linear range of 1-1000nM for simvastatin acid and lovastatin acid, and a linear range of 0.1-100nM for the other analytes in human plasma. The accuracy and the within- and between-day precisions of the assay were within acceptable ranges, and the method was successfully utilized to quantify the statins and their metabolites in human plasma samples collected from an ongoing pharmacokinetic study.